**************
***SURVEY 1***
**************

*Main Figure 3
ciplot norms, by(USother) xline(0) hor
ttest norms, by(USother)
ciplot China_prej, by(USother) xline(0) hor
ttest China_prej, by(USother)

*Appendix Table 8
iebaltab male u_35 han_eth muslim high_ed urban, grpvar(USother) browse
*Table 9
ttest norms1, by(USother)
ttest norms2, by(USother)
ttest norms3, by(USother)

*Table 10
ttest China_prej if high_ed==1, by(USother)
ttest China_prej if high_ed==0, by(USother)
ttest China_prej if US_good==1, by(USother)
ttest China_prej if US_good==0, by(USother)
ttest China_prej if male==1, by(USother)
ttest China_prej if male==0, by(USother)
ttest China_prej if u_35==1, by(USother)
ttest China_prej if u_35==0, by(USother)
ttest norms if high_ed==1, by(USother)
ttest norms if high_ed==0, by(USother)
ttest norms if US_good==1, by(USother)
ttest norms if US_good==0, by(USother)
ttest norms if male==1, by(USother)
ttest norms if male==0, by(USother)
ttest norms if u_35==1, by(USother)
ttest norms if u_35==0, by(USother)

*Table 11
reg China_prej USother high_ed urban male u_35 han_eth muslim, r
ologit norms USother high_ed urban male u_35 han_eth muslim, nolog

*Table 12
ttest China_prej if Duration>180, by(USother)
ttest norms if Duration>180, by(USother)



**************
***SURVEY 2***
**************

*Main Figure 4
ciplot norms, by(MIN_DO_r) xline(0) hor
ttest norms, by(US_t)
ciplot China_prej, by(MIN_DO_r) xline(0) hor
ttest China_prej, by(US_t)

*Appendix Table 13
iebaltab male u_30 han_eth muslim high_ed urban, grpvar(MIN_DO) browse

*Figure 1
ciplot USview_R Iranview_R, by(MIN_DO_r) xline(0) hor
ttest USview_R, by(US_t)
ciplot nationalism_R, by(MIN_DO_r) xline(0) hor
ttest nationalism_R, by(US_t)

*Table 14
ttest racismillegal_R, by(US_t) 
ttest PrefTre_R, by(US_t) 
ttest WorkEd_R, by(US_t)

*Table 15
reg China_prej US_t high_ed urban male u_30 han muslim, r
ologit norms US_t high_ed urban male u_30 han muslim, nolog

*Table 16
ttest China_prej if attention==1, by(US_t) 
ttest norms if attention==1, by(US_t) 
ttest China_prej if Durationinseconds>=180, by(US_t) 
ttest norms if Durationinseconds>=180, by(US_t) 

*Table 17
ttest China_prej if high_ed==1, by(US_t)
ttest China_prej if high_ed==0, by(US_t)
ttest China_prej if urban==1, by(US_t)
ttest China_prej if urban==0, by(US_t)
ttest China_prej if male==1, by(US_t)
ttest China_prej if male==0, by(US_t)
ttest China_prej if u_30==0, by(US_t)
ttest China_prej if u_30==1, by(US_t)
ttest norms if high_ed==1, by(US_t)
ttest norms if high_ed==0, by(US_t)
ttest norms if urban==1, by(US_t)
ttest norms if urban==0, by(US_t)
ttest norms if male==1, by(US_t)
ttest norms if male==0, by(US_t)
ttest norms if u_30==0, by(US_t)
ttest norms if u_30==1, by(US_t)

*Table 18
ttest prej_over50, by(US_t)
ttest norms_overmean, by(US_t)
 
*Table 19
sum nonrep_disc nonrep_norms nonrep_mus nonrep_blk nonrep_nat if Finished==1

*Table 20
ttest nonrep_disc, by(US_t) 
ttest nonrep_norms, by(US_t) 

*Table 21
ttest marrymuslim, by(US_t) 
ttest marrybudd, by(US_t)
ttest marrywhite, by(US_t) 
ttest marryblack, by(US_t) 

*Table 22
reg China_prej USracism nationalism_R high_ed urban male u_30 han muslim if US_t==1, r
ologit norms USracism nationalism_R high_ed urban male u_30 han muslim if US_t==1, nolog
